Analytics Engineer IV, ACV Capital

Who are we looking for:

The Senior Analytics Engineer on the ACV Capital team is an expert practitioner who transforms raw data into trusted, decision-ready models and reports that drive the lending business forward. Sitting at the intersection of data engineering and business intelligence, this role owns the full analytics stack - from dbt model design and data quality to Omni BI dashboards - and partners directly with Capital leadership to surface insights on lead targeting, loan origination, account management, dealer servicing, and operational compliance.
A key objective of this role is reducing ad-hoc analytical bottlenecks over time. You will be expected to answer urgent business questions quickly and directly, while systematically building the underlying dbt models, metric definitions, and BI layer in a way that enables self-serve analytics - including AI-assisted querying - so that Capital stakeholders can answer common questions themselves.

What you will do (Responsibilities):
Analytics Modeling & Data Quality

Design, build, and maintain dbt models (staging, intermediate, production layers) that serve as the single source of truth for Capital KPIs, with machine-readability in mind

Enforce data quality through dbt tests, source freshness checks, and documentation so downstream consumers can trust what they see

Write complex SQL transformations on large datasets; optimize for cost and performance

Reporting & BI

Translate business questions into well-scoped analytical requirements; define metrics in collaboration with Capital leadership and keep definitions governed in our semantic layer

Build and own the Omni BI semantic layer, enabling self-serve chat and dealer-facing embedded reporting

Balance responsiveness to ad-hoc requests while optimizing via building: triage what should be answered once vs. what should be codified so stakeholders or AI tools can self-serve it in the future

Deliver clear, compelling data narratives to non-technical stakeholders; support follow-on questions and iterate quickly

Capital Business Domains

Lead Targeting: develop models and dashboards that identify high-propensity dealer and borrower segments to support outbound sales strategy

Loan Origination Tracking: build funnel visibility from application through funding; surface bottlenecks and conversion opportunities

Operational Functions: provide analytical support for account management workflows, dealer servicing SLAs, and audit/compliance reporting

Project Ownership & Stakeholder Partnership

Own analytical initiatives end-to-end: identify stakeholders, define scope and timelines, and execute without requiring close supervision

Proactively surface opportunities and deliver data-driven recommendations - not just answers to questions that were asked

Navigate competing priorities across multiple stakeholder groups; propose win-win solutions when technical requirements conflict

What you will need (Skills, Experience, Education):
Education

BA/BS in Statistics, Mathematics, Computer Science, Operations Research, or related

Master's or Ph.D. a plus, but offset by demonstrated experience and a deep toolbox

Experience

5+ years of professional experience in analytics engineering, data engineering, or BI

Hands-on production experience with dbt (model design, testing, documentation, incremental strategies)

Proficiency building semantic layers;
Omni or Looker BI experience preferred, but similar experience considered

Expert-level SQL; comfortable with window functions, complex joins, and query optimization in Big Query or a comparable cloud warehouse

Experience delivering major analytical initiatives independently, from scoping through stakeholder presentation

Background in financial services, fintech, or lending is a meaningful plus - familiarity with origination, account management, or B2B lending workflows accelerates ramp

Experience with Git-based version control workflows

Soft Skills

Communicates analytical findings clearly to non-technical audiences

Comfortable navigating ambiguity

Collaborative, low-ego, and invested in the team's collective output

Strong instinct for knowing when to answer quickly vs. when to build properly

Nice-to-Haves

Experience with Google Cloud Platform

Familiarity with AI-assisted analytics or developer workflows

Exposure to credit risk, payment systems, or audit/compliance reporting contexts

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